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Physical Review A

Information reconciliation for phase shift keying discrete modulation continuous-variable quantum key distribution

Zhenguo Lu, Weilin Liu, Yu Zhang, Zengliang Bai, Yongmin Li

Published Nov 19, 2025• 2 citations
Publisher

Abstract

Discrete modulation continuous-variable quantum key distribution protocols are compatible with modern coherent optical communication technologies and devices. As a key part of the protocol, the performance of information reconciliation directly affects the secret key rate and transmission distance. Herein, we propose a reconciliation scheme for hard-decision strategy--based discrete modulation continuous-variable quantum key distribution protocol with eight-phase shift keying by combining slice reconciliation and raptor-like low-density parity-check (RL-LDPC) codes. We design the optimal binary sequence encoding of the discretized values of the receiver and sender, which reduce both the number of levels of error correction and the reconciliation complexity. In order to reduce the frame error rate, both the degree distribution and the size of the base matrix of RL-LDPC code is optimized. Simulation results show that the proposed scheme can reach reconciliation efficiencies of 92.05% and 93% with frame error rates of 6.2% and 11.7% at the signal-to-noise ratio of 0.15, respectively. At these points, the key rates can reach 0.0193 and 0.0195 bits/pulse, respectively.

DOI
10.1103/kgpx-krj7

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Discrete modulation continuous-variable quantum key distribution protocols are compatible with modern coherent optical communication technologies and devices. As a key part of the protocol, the performance of information reconciliation directly affects the secret key rate and transmission distance. Herein, we propose a reconciliation scheme for hard-decision strategy--based discrete modulation continuous-variable quantum key distribution protocol with eight-phase shift keying by combining slice reconciliation and raptor-like low-density parity-check (RL-LDPC) codes. We design the optimal binary sequence encoding of the discretized values of the receiver and sender, which reduce both the number of levels of error correction and the reconciliation complexity. In order to reduce the frame error rate, both the degree distribution and the size of the base matrix of RL-LDPC code is optimized. Simulation results show that the proposed scheme can reach reconciliation efficiencies of 92.05% and 93% with frame error rates of 6.2% and 11.7% at the signal-to-noise ratio of 0.15, respectively. At these points, the key rates can reach 0.0193 and 0.0195 bits/pulse, respectively.
In continuous-variable (CV) quantum key distribution (QKD), the reconciliation efficiency and frame error rate of the information reconciliation have a significant impact on the secret key rate. For a fixed-rate multiedge-type low-density parity-check (LDPC) code, the reconciliation efficiency and frame error rate will inevitably vary due to the fluctuations of the signal-to-noise ratio (SNR) of the CV QKD system, which degrades the performance of the system. We propose a high-efficiency rate-adaptive information reconciliation scheme by combining raptorlike (RL) LDPC codes with the addition of trusted noises. We establish the model of adding trusted noises and combine it with the RL LDPC codes to optimize the secret key rate under the time-varying channel. The simulation results show that our scheme can maintain a high reconciliation efficiency of more than 94.4% and a low frame error rate within 15% fluctuation range of the SNR. Furthermore, we implement the hardware acceleration of the proposed rate-adaptive scheme on a graphics processing unit and achieve a decoding throughput of 65.5 Mbits/s by optimizing the storage of the parity-check matrix. Our results are useful for the practical CV QKD under the realistic time-varying channel.
Abstract In continuous-variable quantum key distribution systems, reconciliation is a crucial step that significantly affects the secret key rate (SKR). The rateless protocol based on Raptor codes can achieve high reconciliation efficiency at low signal-to-noise ratios (SNRs). However, the high complexity of low-density parity-check (LDPC) codes used for the precoding in Raptor codes limits the speed of reconciliation. In this paper, we propose an adaptive reconciliation protocol by modifying Raptor codes. The length of random binary sequences is increased because we remove the LDPC precoding that adds redundancy. The modified Raptor codes reduce the complexity of encoding with better performance. The proposed protocol gives a reconciliation efficiency higher than 98.1% in the SNR below −20 dB and maintains a certain SKR in long-distance transmission.
An information reconciliation method for continuous-variable quantum key distribution with Gaussian modulation that is based on non-binary low-density parity-check (LDPC) codes is presented. Sets of regular and irregular LDPC codes with different code rates over the Galois fields GF(8)GF(8)GF(8), GF(16)GF(16)GF(16), GF(32)GF(32)GF(32), and GF(64)GF(64)GF(64) have been constructed. We have performed simulations to analyze the efficiency and the frame error rate using the sum-product algorithm. The proposed method achieves an efficiency between 0.940.940.94 and 0.980.980.98 if the signal-to-noise ratio is between 444 dB and 242424 dB.
In continuous-variable quantum key distribution (CV-QKD), the information reconciliation step plays a crucial role in ensuring the security and efficiency of the key exchange process. This paper investigates the use of heuristic and reinforcement learning-based methods to adaptively adjust the low-density parity check (LDPC) code rate in response to the time-varying channel signal-noise-ratio (SNR), with the goal of maximizing the final key rate. Leaving the SNR to fluctuate by ±1dB around a fixed value, we analyze the trade-off between the reconciliation efficiency and the frame error rate (FER). We propose a rate-adaptive reconciliation scheme that leverages reinforcement learning to select the optimal LDPC code rate, comparing its performance against traditional fixed-rate approaches. The results demonstrate that the proposed adaptive scheme significantly enhances the key rate and shows potential in applying for a wide range of SNR.
Abstract Quantum key distribution (QKD) is the most mature application of quantum information technology. Information reconciliation is a crucial step in QKD and significantly affects the final secret key rates shared between two legitimate parties. We analyze and compare various construction methods of low-density parity-check (LDPC) codes and design high-performance irregular LDPC codes with a block length of 10 6 . Starting from these good codes and exploiting the slice reconciliation technique based on multilevel coding and multistage decoding, we realize high-efficiency Gaussian key reconciliation with efficiency higher than 95% for signal-to-noise ratios above 1. Our demonstrated method can be readily applied in continuous variable QKD.
Due to the rapid development of quantum computing technology, encryption systems based on computational complexity are facing serious threats. Based on the fundamental theorem of quantum mechanics, continuous-variable quantum key distribution (CVQKD) has the property of physical absolute security and can effectively overcome the dependence of the current encryption system on the computational complexity. In this paper, we construct the spatially coupled (SC)-low-density parity-check (LDPC) codes and quasi-cyclic (QC)-LDPC codes by adopting the parity-check matrices of LDPC codes in the Advanced Television Systems Committee (ATSC) 3.0 standard as base matrices and introduce these codes for information reconciliation in the CVQKD system in order to improve the performance of reconciliation efficiency, and then make further improvements to final secret key rate and transmission distance. Simulation results show that the proposed LDPC codes can achieve reconciliation efficiency of higher than 0.96. Moreover, we can obtain a high final secret key rate and a long transmission distance through using our proposed LDPC codes for information reconciliation.